Robin Senge

859 citations
20 papers · 646 · h-index 12

Impact in

    • Text and Document Classification Technologies
    • Machine Learning and Data Classification
    • Fuzzy Logic and Control Systems
    • Advanced Clustering Algorithms Research

Papers in

    • Fuzzy Logic and Control Systems 7
    • Neural Networks and Applications 5
    • Data Stream Mining Techniques 2
    • Machine Learning and Data Classification 2
    • Data Mining Algorithms and Applications 3

Robin Senge

19 papers receiving 634 citations

Peers

Robin Senge
Comparison fields: 5 of 108
  • Artificial Intelligence 377
  • Signal Processing 74
  • Management Science and Operations Research 84
  • Virology 26
  • Information Systems 118
Replace Ramgopal R. Mettu with:
Ramgopal R. Mettu United States
Xinghao Pan United States
Hwanjo Yu South Korea
Kun-Ta Chuang Taiwan
Abbas Kazerouni United States
Dariusz Brzeziński Poland
Hechang Chen China
Mohan Timilsina Ireland
Xiaolan Xie China
Junzhong Gu China
Robin Senge relative to Ramgopal R. Mettu United States Ramgopal R. Mettu's profile →
Citations per field
00.5×9.1×
Ramgopal R. Mettu · 1×
Citations per year

Countries citing papers authored by Robin Senge

Since Specialization
Citations

This map shows the geographic impact of Robin Senge's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Robin Senge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robin Senge more than expected).

Fields of papers citing papers by Robin Senge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robin Senge. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Robin Senge. The network helps show where Robin Senge may publish in the future.

Co-authors

The 19 scholars most cited alongside Robin Senge, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Robin Senge Line = papers co-authored together Robin Senge links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 2013126
2 201395
3 201189
4 201363
5 201059
6 201343
7 201938
8 201231
9 202130
10 201625
11 201515
12 201012
13 20118
14 20135
15
Learning Pattern Tree Classifiers Using a Co-Evolutionary Algorithm.
20092
16 20192
17 20121
18 20131
19 20141
20 20230

About Robin Senge

Robin Senge is a scholar working on Artificial Intelligence, Information Systems, Marketing, Computational Theory and Mathematics and Management Science and Operations Research, having authored 20 papers that have together received 646 indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (7 papers), Neural Networks and Applications (5 papers), Data Mining Algorithms and Applications (3 papers), Rough Sets and Fuzzy Logic (3 papers), Forecasting Techniques and Applications (3 papers), Consumer Market Behavior and Pricing (3 papers), Data Stream Mining Techniques (2 papers) and Machine Learning and Data Classification (2 papers). The work is most often cited by research in Artificial Intelligence (377 citations), Signal Processing (74 citations), Management Science and Operations Research (84 citations), Virology (26 citations) and Information Systems (118 citations). Robin Senge has collaborated with scholars based in Germany, United States and Spain. Frequent co-authors include Eyke Hüllermeier, Juan José del Coz, Maria Rifqi, Dominik Heider, José Ramón Quevedo, Elena Montañés, Weiwei Cheng, Oliver Hirsch, Norbert Donner‐Banzhoff and Krzysztof Dembczyński. Their work appears in journals such as IEEE Transactions on Fuzzy Systems, Information Sciences, Bioinformatics, European Journal of Operational Research and International Journal of Forecasting.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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